kalshi_probability

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the full behavioral burden. It does disclose useful context — free, no signup required (no auth needed) and that category queries return the most active open markets. It says nothing about pagination, rate limits, error behavior, or the shape of a probability result, leaving meaningful gaps for a data tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The core sentence and example are front-loaded and useful, but 'Free, no signup required' is duplicated verbatim in the first line, which is pure waste. Removing the repetition would make this tight.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotations, so the description is the only source of behavioral and return-value context. It gives a partial picture of returns ('most active open markets') and access terms, but omits result fields and constraints an agent would want before calling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents limit, ticker, and category (including the enumerated category values and the required-either constraint). The description merely restates the category/ticker axis and adds no format or constraint detail beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: querying Kalshi prediction-market probabilities, with the two supported query modes (category vs. ticker). It also notes what a category query returns (most active open markets). However, it never distinguishes itself from the sibling kalshi_market tool, so an agent must guess which to pick.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It implies usage via 'Query by category ... or a specific market ticker' and the example call, so the two modes are discoverable. But there is no explicit when-to-use guidance, no when-not-to-use, and no routing to the kalshi_market sibling that overlaps this domain.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.